Grey-Box Identification Based on Horizon Estimation and Nonlinear Optimization
2009 (English)In: Proceedings of the 41st ISCIE International Symposium on Stochastic Systems, Institute of Systems, Control and Information Engineers , 2009, 1-6 p.Conference paper (Refereed)
In applications of (nonlinear) model predictive control a more and more common approach for the state estimation is to use moving horizon estimation, which employs (nonlinear) optimization directly on a model for a whole batch of data. This paper shows that horizon estimation may also be used for joint parameter estimation and state estimation, as long as a bias correction based on the Kalman ﬁlter is included. A procedure how to approximate the bias correction for nonlinear systems is outlined.
Place, publisher, year, edition, pages
Institute of Systems, Control and Information Engineers , 2009. 1-6 p.
Grey-box, Identification, Estimation, Nonlinear, Optimization
IdentifiersURN: urn:nbn:se:liu:diva-95544ISBN: 9784915740473OAI: oai:DiVA.org:liu-95544DiVA: diva2:635905
41st ISCIE International Symposium on Stochastic Systems, Kobe, Japan, 13-14 November, 2009